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Lean Management and Industry 4.0: a dynamic capabilities framework for an integrated transformation

Abstract

This study addresses the ongoing challenge of concurrently integrating Lean and Industry 4.0, a critical need for companies striving to enhance operational capabilities in increasingly digital environments. While past research focused on sequential approaches or high-level conceptualizations, this research delves into the level of ‘how’, applying Dynamic Capabilities theory through a deductive, four-stage mixed-method design, focused on large German manufacturing firms. First, expert interviews underwent thematic analysis to identify strategies and courses of action for integration. Next, an exploratory survey refined these results statistically. Third, the findings were validated and triangulated via a Delphi study, from which a structured integration framework emerged. Finally, confirmatory composite analysis of 236 managerial responses confirmed the reliability and validity of the framework. The study presents 44 validated actions grouped into six dimensions: Initiating, Sensing, Seizing, Transforming, Resources and Capabilities. Notably, it introduces the new ‘Initiating’ dimension, expanding the Dynamic Capabilities theory. While the study’s focus on large German manufacturers is a limitation, the resulting framework offers practical pathways for companies unable to pursue sequential integration due to time pressures. Ultimately, this research provides both theoretical advancement and practical tools for successfully managing the simultaneous transformation towards Lean and Industry 4.0.
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Category

Academic article

Language

English

Author(s)

  • Tim Komkowski
  • Jiju Antony
  • Fabiane Letícia Lizarelli
  • Leopoldo Gutierrez
  • Michael Sony
  • Daryl Powell
  • Tanawadee Pongboonchai-Empl
  • Jose Arturo Garza-Reyes
  • Luis Ignacio Araos Acharan

Affiliation

  • SINTEF Industry / SINTEF Manufacturing
  • University of Granada
  • Heriot-Watt University
  • Oxford Brookes University
  • University of Derby
  • University of Northumbria at Newcastle
  • University of Kiel
  • University of South-Eastern Norway
  • India
  • Federal University of São Carlos

Year

2026

Published in

Production planning & control (Print)

ISSN

0953-7287

Page(s)

1 - 22

View this publication at Norwegian Research Information Repository